X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=epclust%2FR%2FcomputeSynchrones.R;h=3c1959a62433282034a6176b8ec4b5c79f4b6af4;hb=dc86eb0c992e6e4ab119d48398d040c4cf3a75fd;hp=16bf0b44939fcd760b52ed5fff693e52a4dcfcee;hpb=282342bafdc9ff65c5df98c6e2304d63b33b9fb2;p=epclust.git

diff --git a/epclust/R/computeSynchrones.R b/epclust/R/computeSynchrones.R
index 16bf0b4..3c1959a 100644
--- a/epclust/R/computeSynchrones.R
+++ b/epclust/R/computeSynchrones.R
@@ -1,33 +1,22 @@
 #' computeSynchrones
 #'
-#' Compute the synchrones curves (sum of clusters elements) from a matrix of medoids,
+#' Compute the synchrones curves (sums of clusters elements) from a matrix of medoids,
 #' using euclidian distance.
 #'
-#' @param medoids matrix of medoids in columns (curves of same length as the series)
-#' @param getSeries Function to retrieve series (argument: 'indices', integer vector)
+#' @param medoids matrix of K medoids curves in columns
 #' @param nb_curves How many series? (this is known, at this stage)
 #' @inheritParams claws
+#' @inheritParams computeWerDists
 #'
 #' @return A matrix of K synchrones in columns (same length as the series)
 #'
 #' @export
 computeSynchrones <- function(medoids, getSeries, nb_curves,
-	nb_series_per_chunk, ncores_clust=1,verbose=FALSE,parll=TRUE)
+	nb_series_per_chunk, ncores=3, verbose=FALSE, parll=TRUE)
 {
 	# Synchrones computation is embarassingly parallel: compute it by chunks of series
 	computeSynchronesChunk <- function(indices)
 	{
-		if (parll)
-		{
-			require("bigmemory", quietly=TRUE)
-			requireNamespace("synchronicity", quietly=TRUE)
-			require("epclust", quietly=TRUE)
-			# The big.matrix objects need to be attached to be usable on the workers
-			synchrones <- bigmemory::attach.big.matrix(synchrones_desc)
-			medoids <- bigmemory::attach.big.matrix(medoids_desc)
-			m <- synchronicity::attach.mutex(m_desc)
-		}
-
 		# Obtain a chunk of reference series
 		series_chunk <- getSeries(indices)
 		nb_series_chunk <- ncol(series_chunk)
@@ -56,20 +45,9 @@ computeSynchrones <- function(medoids, getSeries, nb_curves,
 	# NOTE: synchronicity is only for Linux & MacOS; on Windows: run sequentially
 	parll <- (parll && requireNamespace("synchronicity",quietly=TRUE)
 		&& Sys.info()['sysname'] != "Windows")
+
 	if (parll)
-	{
 		m <- synchronicity::boost.mutex() #for lock/unlock, see computeSynchronesChunk
-		# mutex and big.matrix objects cannot be passed directly:
-		# they will be accessed from their description
-		m_desc <- synchronicity::describe(m)
-		synchrones_desc <- bigmemory::describe(synchrones)
-		medoids <- bigmemory::as.big.matrix(medoids)
-		medoids_desc <- bigmemory::describe(medoids)
-		# outfile=="" to see stderr/stdout on terminal
-		cl <- parallel::makeCluster(ncores_clust, outfile="")
-		parallel::clusterExport(cl, envir=environment(),
-			varlist=c("synchrones_desc","m_desc","medoids_desc","getSeries"))
-	}
 
 	if (verbose)
 		cat(paste("--- Compute ",K," synchrones with ",nb_curves," series\n", sep=""))
@@ -78,12 +56,12 @@ computeSynchrones <- function(medoids, getSeries, nb_curves,
 	indices_workers <- .splitIndices(seq_len(nb_curves), nb_series_per_chunk)
 	ignored <-
 		if (parll)
-			parallel::parLapply(cl, indices_workers, computeSynchronesChunk)
+		{
+			parallel::mclapply(indices_workers,
+				function(inds) computeSynchronesChunk(inds), mc.cores=ncores)
+		}
 		else
 			lapply(indices_workers, computeSynchronesChunk)
 
-	if (parll)
-		parallel::stopCluster(cl)
-
 	return (synchrones[,])
 }